| porsTOST {BayesRepDesign} | R Documentation |
Probability of replication success based on TOST equivalence
Description
This function computes the probability to achieve replication success based on establishing the absence of a practically relevant effect size with the Two One-Sided Tests (TOST) procedure in the replication study.
Usage
porsTOST(level, dprior, margin, sr)
Arguments
level |
Significance level for the TOST p-value |
dprior |
Design prior object |
margin |
The equivalence margin > 0 for the equivalence region around zero that defines a region of practically irrelevant effect sizes |
sr |
Replication standard error |
Value
The probability to achieve replication success
Author(s)
Samuel Pawel
References
Pawel, S., Consonni, G., and Held, L. (2022). Bayesian approaches to designing replication studies. arXiv preprint. doi:10.48550/arXiv.2211.02552
Anderson, S. F. and Maxwell, S. E. (2016). There's more than one way to conduct a replication study: Beyond statistical significance. Psychological Methods, 21(1), 1-12. doi:10.1037/met0000051
Examples
## specify design prior
to1 <- 2
so1 <- 0.05
dprior <- designPrior(to = to1, so = so1, tau = 0.1)
porsTOST(level = 0.1, dprior = dprior, margin = 0.3, sr = c(0.05, 0.03))